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A Generative Adaptive Convolutional Neural Network with Attention Mechanism for Driver Fatigue Detection with Class-Imbalanced and Insufficient Data

https://doi.org/10.2139/ssrn.4657697
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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/s00521-020-05467-5openalex-extracted
Innovative deep learning models for EEG-based vigilance detection
inferredcites →https://doi.org/10.1007/s11818-008-0351-yopenalex-extracted
Automatic EOG analysis: A first step toward automatic drowsiness scoring during wake-sleep transitions
inferredcites →https://doi.org/10.1016/j.jsr.2009.04.005openalex-extracted
Predicting driver drowsiness using vehicle measures: Recent insights and future challenges
inferredcites →https://doi.org/10.1016/j.neucom.2019.05.108openalex-extracted
Driver sleepiness detection from EEG and EOG signals using GAN and LSTM networks
inferredcites →https://doi.org/10.1016/j.ssci.2008.01.007openalex-extracted
Can SVM be used for automatic EEG detection of drowsiness during car driving?
inferredcites →https://doi.org/10.1038/s41592-018-0261-2openalex-extracted
U-Net: deep learning for cell counting, detection, and morphometry
inferredcites →https://doi.org/10.1046/j.1469-8986.2003.00130.xopenalex-extracted
Awareness of sleepiness when driving
inferredcites →https://doi.org/10.1088/1741-2552/aa5a98openalex-extracted
A multimodal approach to estimating vigilance using EEG and forehead EOG
inferredcites →https://doi.org/10.1109/access.2017.2779939openalex-extracted
LSTM Fully Convolutional Networks for Time Series Classification
inferredcites →https://doi.org/10.1109/access.2021.3100478openalex-extracted
Fatigue Detection in SSVEP-BCIs Based on Wavelet Entropy of EEG
inferredcites →https://doi.org/10.1109/ijcnn.2017.7966039openalex-extracted
Time series classification from scratch with deep neural networks: A strong baseline
inferredcites →https://doi.org/10.1109/jstars.2020.3009352openalex-extracted
Channel-Attention-Based DenseNet Network for Remote Sensing Image Scene Classification
inferredcites →https://doi.org/10.1109/lgrs.2020.3041530openalex-extracted
L-UNet: An LSTM Network for Remote Sensing Image Change Detection
inferredcites →https://doi.org/10.1109/tits.2021.3098309openalex-extracted
Driver Mental Fatigue Detection Based on Head Posture Using New Modified reLU-BiLSTM Deep Neural Network
inferredcites →https://doi.org/10.1109/tits.2022.3176973openalex-extracted
A Multimodal Fusion Fatigue Driving Detection Method Based on Heart Rate and PERCLOS
inferredcites →https://doi.org/10.1109/tnnls.2018.2886414openalex-extracted
EEG-Based Spatio–Temporal Convolutional Neural Network for Driver Fatigue Evaluation
inferredcites →https://doi.org/10.1109/tnnls.2022.3147208openalex-extracted
EEG-Based Cross-Subject Driver Drowsiness Recognition With an Interpretable Convolutional Neural Network
inferredcites →https://doi.org/10.1109/tpami.2016.2572683openalex-extracted
Fully Convolutional Networks for Semantic Segmentation
inferredcites →https://doi.org/10.1109/tpami.2019.2913372openalex-extracted
Squeeze-and-Excitation Networks
inferredcites →https://doi.org/10.1109/tsmc.2019.2956022openalex-extracted
A Complex Network-Based Broad Learning System for Detecting Driver Fatigue From EEG Signals
inferredcites →https://doi.org/10.1162/neco.1997.9.8.1735openalex-extracted
Long Short-Term Memory
inferredcites →https://doi.org/10.14661/2015.1073-1077openalex-extracted
Presenting a model for dynamic facial expression changes in detecting drivers' drowsiness.
inferredcites →https://doi.org/10.2333/bhmk.18.30_23openalex-extracted
On the Brain Wave Activity of Professional Drivers During Monotonous Work
inferredcites →https://doi.org/10.3390/sym11010001openalex-extracted
Fundus Image Classification Using VGG-19 Architecture with PCA and SVD
inferredcites →https://doi.org/10.48550/arxiv.1406.2661openalex-extracted
Generative Adversarial Networks
inferredcites →https://doi.org/10.48550/arxiv.1412.6980openalex-extracted
Adam: A Method for Stochastic Optimization
inferredcites →https://doi.org/10.48550/arxiv.1502.03167openalex-extracted
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
inferredcites →https://doi.org/10.48550/arxiv.1809.06534openalex-extracted
Multi-channel EEG recordings during a sustained-attention driving task
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